Learning method and system using detached sensor

ABSTRACT

One embodiment includes a computer-implemented method using a window environment of a display, with a detached imaging sensor, to enable a user to learn. Another embodiment includes a computer-implemented system helping a user learn using a detached imaging sensor. In yet another embodiment, a computer-implemented system monitors automatically more than once a user&#39;s behavior while the user is working on materials. Through monitoring the user&#39;s volitional or involuntary behavior, the system determines whether to change what is to be presented by the display. The change could include providing rewards, punishments, and stimulation; or changing the materials. The system can also react by asking the user a question. Based on the user&#39;s response, the system may change to more appropriate materials, or different presentation styles.

CROSS-REFERENCE TO RELATED APPLICATIONS

This is a continuation of co-pending U.S. patent application Ser. No.13/481,821, filed on May 26, 2012, which is a continuation of co-pendingU.S. patent application Ser. No. 10/694,706, filed on Oct. 28, 2003,which is a continuation of U.S. Pat. No. 6,699,043, filed on Jan. 14,2002, which is a continuation of U.S. patent application Ser. No.09/385,795, filed on Aug. 30, 1999, since abandoned, which is acontinuation of U.S. patent Ser. No. 08/689,678, filed on Aug. 13, 1996,now U.S. Pat. No. 5,944,530; all incorporated by reference into thisapplication.

BACKGROUND OF THE INVENTION

The present invention relates generally to learning via a computingdevice, and more particularly to learning method and system usingdetached sensor.

Both at home and in schools, the computer is gradually becoming a majormedium for education. There are many different reasons for this trend.One is the tremendous reduction in the price of a computer, causing itto permeate into almost every household. Though the price of a computerhas been dropping, its computation and memory capacity have increasedmany folds, leading to computer programs with significantly moreintelligence and improved user-friendliness. Another reason is that acomputer-aided-education system can be very personalized; it can betailored to the strengths and weaknesses of individual students. This isvery hard to achieve in today's educational environment, in part due tothe increase in the students-per-instructor ratio. Though computer-aidededucation system could be very useful, there is still a need for asystem and method that could sense a student in a better manner.

SUMMARY OF THE INVENTION

One embodiment of the invention includes computer-implemented method andsystem using a window environment of a display, with at least onedetached sensor, to enable a user to learn. Another embodiment provideslearning methods and systems that help a user learn using at least onedetached imaging sensor. In yet another embodiment, the presentinvention provides a computer-aided-educational system and method thatautomatically consider a student's concentration-sensitive behaviorwhile the student is working on materials.

In one embodiment, the present invention includes a display, aprocessor, and a detached imaging sensor to sense a first feature fromthe head of a user regarding a first volitional behavior of the user toproduce a first set of data. The embodiment is further configured tosense a second feature of the user regarding a second volitionalbehavior of the user to produce a second set of data, the second featurenot from the head of the user. The processor is configured to analyzethe first set and the second set of data, with the analyzing beingdepending on the display, and to determine whether to change what is tobe presented by the display in view of the analyzing to enable the userto learn.

In one embodiment, the present invention includes a presenter, anon-intrusive sensor, a controller and an indicator. The presenterpresents study materials on a subject to the student; the non-intrusivesensor automatically monitors more than once the student'sconcentration-sensitive behavior while the student is working on thematerials; the controller analyzes the student's concentration-sensitivebehavior based on one or more rules; and the indicator provides anindication on the student's concentration level based on the analysis.In another embodiment, the present invention reacts according to theindication.

There are a number of examples of the concentration-sensitive behaviorthat the sensor can monitor. In one embodiment, the sensor monitors thestudent's volitional behavior, such as his inputs into the computer, hisfacial expressions, his facial orientations and his eyes. In anotherembodiment, the sensor monitors the student's involuntary behavior, suchas the sizes of his pupils.

The controller analyzes one or more of the above behavior based on oneor more rules. These rules are similar to the instructor's “intuition.”For example, one rule is as follows: The student has lost concentrationin the study materials if for a predetermined period of time, thestudent's inputs through a mouse have been in a window that does notcontain study materials. Another rule is that if the student is notlooking at the monitor showing the study materials for a predeterminedperiod of time, the student has lost concentration in the studymaterials. From the analysis, the system provides an indication on thestudent's concentration level.

Based on the indication, the system could react accordingly. Differentreactions are applicable. Some examples include rewards, punishments,stimulation, and changing the study materials.

In another embodiment, due to the indication, the system asks thestudent a question, which can stimulate the student and can assess thestudent's understanding level in the study materials. From the student'sresponse to the question, the system may change to more appropriatestudy materials and/or presentation style.

The question-asking approach in the above embodiment does not have to bea reaction to the indication. In one embodiment, as the system ispresenting study materials to the student, unexpected by the student,the system asks the student a question. After the student responds tothe question, the system resumes back to present study materials to thestudent. In such an embodiment, the question tends to increase theconcentration level of the student in the study materials.

In yet another embodiment, the present invention also includes acalibrator, which calibrates the student's concentration-sensitivebehavior before the behavior is being monitored to show concentration.One type of calibration establishes the student's behavior when thestudent is paying attention, and compares it with the student's behaviorwhen the student is working on the study materials. Calibrationtypically improves the accuracy of the system.

Other aspects and advantages of the present invention will becomeapparent from the following detailed description, which, when taken inconjunction with the accompanying drawings, illustrates by way ofexample the principles of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows one embodiment of the present invention.

FIGS. 2A-B show one embodiment of a system implementing the presentinvention.

FIG. 3 shows a set of steps to implement one embodiment of the presentinvention.

FIG. 4 shows examples of volitional behavior monitored by the sensor inthe present invention.

FIG. 5 shows another embodiment of the present invention.

Same numerals in FIGS. 1-5 are assigned to similar elements in all thefigures. Embodiments of the invention are discussed below with referenceto FIGS. 1-5. However, those skilled in the art will readily appreciatethat the detailed description given herein with respect to these figuresis for explanatory purposes as the invention extends beyond theselimited embodiments.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 shows one embodiment of a computer-aided-educational system 100of the present invention. As an overview of some of its components, thesystem 100 includes a selector 102, which selects study materials from astudy-materials storage medium 108 to be presented to a student througha presenter 106. While the student is working on the study materials, anon-intrusive sensor 110 monitors the student's concentration-sensitivebehavior, and sends its results back to a controller 104. Then thecontroller 104 based on one or more rules from a rules storage medium112 analyzes the monitored results to provide through an indicator 114,an indication on the student's concentration level. In anotherembodiment, the selector is 102 also connected to the controller 104 tokeep track of the study materials presented to the student.

FIG. 2A shows one embodiment of a system 150 implementing the presentinvention, preferably in software and hardware. The system 150 includesa server computer 152 and a number of client computers, such as 154,which can be a personal computer. Each client computer communicates tothe server computer 152 through a dedicated communication link, or acomputer network 156.

FIG. 2B shows one embodiment of a client computer 154. It typicallyincludes a bus 159 connecting a number of components, such as aprocessing unit 160, a main memory 162, an I/O controller 164, aperipheral controller 166, a graphics adapter 168 and a networkinterface adapter 170. The I/O controller 164 is connected tocomponents, such as a harddisk drive 172 and a floppy disk drive 174.The peripheral controller 166 is connected to peripheral components,such as a keyboard 176, a mouse 182, and a digital camera 180. Thegraphics adapter 168 is connected to a monitor 178; and the networkinterface adapter 170 is connected to the network 120. The network canbe the Internet, an intranet, the world wide web and other forms ofnetworks.

Different components of the present invention can be in differentelements shown in FIGS. 2A-B. For example, the presenter 106 and thesensor 110 can be in a client computer; the selector 102, the controller104, the study-materials storage medium 108, the rules storage medium112 and the indicator 114 can be in the server computer 152. In anotherembodiment, the selector 102, the controller 104 and the indicator 114are also in a client computer. Different components can be in differentelements in the above description. Nonetheless, there is no restrictionpreventing all components to reside in one element, such as a clientcomputer. A number of operations in the present invention can beimplemented by software, which is controlled, for example, by theprocessing unit 160. In yet another embodiment, the number of operationsimplemented by software can be stored in a storage-medium, which can be,for example, the main memory 162 or a CD read-only-memory.

The present invention is applicable to teach any subject or materialsthat can be taught by a computer. The teaching period may last onesemester or a year, or just one class session. The materials may coverinter-disciplinary areas, such as electrical engineering andthermodynamics, or computer networking and programming techniques. Thematerials may just be for training a field engineer on a new product. Inthe following, mathematics is the subject used to illustrate the presentinvention.

In one embodiment, the subject is divided into major-topics, with eachmajor-topic subdivided into minor-topics, and with each minor-topicfurther subdivided into line-items. Each line-item typically covers onewell-defined area in the subject. In another embodiment, the subject isfurther divided into more levels below the line-items; and in a thirdembodiment, the subject is just divided into line-items.

As an example of line-items, if the major-topic is high school algebra,then it can be divided into the following line-items, with bracketedterms served as comments:

High School Algebra (the major-topic)

(Minor-topics under the major-topic)

Decimal Numbers

Polynomials

Linear Equations

Quadratic Equations

. . .

Integers

(Line-items under the minor-topic of integers)

Addition & Subtraction (Difficulty level 1)

Multiplication (Difficulty level 2)

Division (Difficulty level 2)

Prime Numbers (Difficulty level 3)

Factorization (Difficulty level 3)

Common Divisor (Difficulty level 4)

. . .

Fractions

(Line-items under the minor-topic of fractions)

Addition & Subtraction (+/−) with Common Denominator

(Difficulty level 3)

+/− with Integers (Difficulty level 4)

+/− without Common Denominator (Difficulty level 5)

Multiplication and Divisions (*,/) with Integers (Difficulty level 5)

*,/ with fraction (Difficulty level 6)

Compound Fractions (Difficulty level 6)

Fraction Reduction (Difficulty level 7)

Ratios and Proportions (Difficulty level 7)

. . .

Another example with the minor topic being differential calculus is asfollows:

Calculus (major topic)

Differential calculus (minor topic)

Fractions (Difficulty level 1)

Polynomials (Difficulty level 1)

Exponential Functions (Difficulty level 1)

Differentiation (Difficulty level 2)

Differentiate a sum (Difficulty level 3)

Differentiate a product (Difficulty level 3)

Differentiate a quotient (Difficulty level 4)

In one embodiment, each line-item has a difficulty level. The bracketeddifficulty level next to each line-item in the above example indicateshow difficult one line-item is relative to other line-items in thesubject, or how significant one is relative to another. A line-item witha low difficulty level is a relatively easy line-item or a relativelyless important line-item. Typically, a student learning a subject startsfrom learning line-items at the lowest difficulty level.

The lists of items in the above examples are generated based on expertknowledge on the subject of mathematics. With the proper instruction,such as through reading the present specification, generating such listswith the difficulty levels should be obvious to experts in the subject.The more knowledgeable the expert, the more complete the sets of items.

In one embodiment, each line-item is represented by a line-item root,which includes the line item and its root. In the above example, theroot of a line-item includes its subject, its major topic and minortopic.

In one embodiment, the selector 102 starts the learning process byselecting a line-item with the lowest difficulty level. If there are anumber of those, one of them is randomly selected. Study materials forthat line-item are retrieved from the study-materials storage medium 108to be presented to the student. After presentation, the selector 102selects another line-item with the lowest difficulty level among all theunselected line-items, and the process repeats. For this embodiment,each line-item also includes a mode attribute, which is changed from theun-selected to the selected mode after the study materials for thatline-item has been selected to be worked on by the student.

To select a set of study materials from the study-material storagemedium 108, the selector 102 sends the line-item root to the storagemedium 108 to retrieve the corresponding study materials. Typically,there are a number of sets of study materials in the storage-medium 108,and they can be in the following format:

(line-item root, mode, study materials)

The following serves as examples of study materials for differentiatingpolynomial:

First, the system teaches the approach to generate derivatives based onthe basic principle in differentiation, such as:

df(x)/dx=lim _(h→0)((f(x+h)−f(x))/h)

Then the system teaches the generalized equation, such as:

((dΣa _(i) x ^(i))/dx)=(Σi*a _(i) x ^(i−1))

Finally, the system teaches the importance of and the way to find optimaand minima by solving the following equation:

((dΣa _(i) x ^(i))/dx)=0

Based on the line-item root, and with one set of study materials perline-item, the selector 102 retrieves from the study-materialsstorage-medium 108, the corresponding set of study materials. Creatingstudy materials on a subject should be obvious to experts in thesubject, and will not be further discussed in this application.

The selector 102 then sends the retrieved study materials to thepresenter 106. The study materials can be a document with no questions,arranged as a list of screens. The presenter 106 typically includes themonitor 178, which presents the study materials to the student, who cango from one screen to another with the keyboard 176, or the mouse 182.In another embodiment, the study materials are broadcast through aradio. As the student is working on the study materials presentedthrough the radio, the student's concentration-sensitive behavior ismonitored automatically.

In another embodiment, the study materials only have questions.Typically, students gain a better understanding on a subject throughactively working on questions than through passively reading studymaterials. In one embodiment, each question is embedded in a questionentry, which is of the following format:

(line-item root, mode, question-body, answer).

The term “question-body” describes the body of a question. The followingserves as an example:

Subject: Mathematics.

Major-topic: High School Algebra.

Minor-topic: Fraction.

Line-item: +/− with common denominator

Mode: Un-selected

Answer Question-body

28/37 What is the sum of 2/37, 3/37, 8/37 and 15/37?

−2/43 17/43−25/43+6/43=?

The selector 102 sends to the study-materials storage medium 108 theline-item root to retrieve the set of questions with the same line-itemroot.

An example of study materials with questions are for the line-item ofdifferentiating exponential functions. A number of questions aregenerated, including the question on expanding an exponential functionbased on Taylor expansion, the question on differentiating theTaylor-expanded exponential function, whose answer is the originalTaylor-expanded exponential function, and the question ondifferentiating the exponential function, whose answer is theexponential function.

In another embodiment, the study materials include study materials withquestions and study materials without questions.

Note that the formats of the study materials may change as the studentprogresses. The student can learn one line-item based on questions, andanother based on study materials with no questions. As an example, fordifferential calculus, of the different line-items, all of them can belearnt through either study materials with or without questions, exceptfor the line-item of differentiation, which is typically learnt withoutquestions. That study-materials cover the general differentiationconcept, such as the following:

df(x)/dx=lim _(h→0)((f(x+h)−f(x))/h)

FIG. 3 shows a set of steps 250 to implement one embodiment of thepresent invention. First, the presenter 106 presents (step 252) theselected study materials to the student. As the student is working onthe study materials, the sensor 110 monitors (step 254) more than oncethe student's concentration-sensitive behavior, and feeds thosemonitored results to the controller. The controller 104 analyzes (step256) the results based on one or more rules to provide (step 258) anindication on the student's concentration. Based on the indication, thesystem reacts (step 260) accordingly.

A type of concentration-sensitive behavior is a type of behavior that issensitive to one's concentration. As one's concentration changes, such atype of behavior changes accordingly. The behavior can be physical,psychological, biological, emotional and physiological.

In the step of monitoring (step 254), the sensor automatically monitorsmore than once the student's concentration-sensitive behavior while thestudent is working on the study materials. Instead of just monitoringonce to determine concentration level, monitoring more than onceincreases the accuracy in determining the student's concentration level.For example, a student is concentrating on the study materials. Amosquito lands on the back of his right hand. As the student is tryingto hit the mosquito, the system monitors him. The indication based onthat image alone is a correct indication of the student's concentrationlevel in the study materials at that specific instant. However, thesingle measurement is not a good indication of the student's actualconcentration level in the study materials—that single measurement is anoutlying point that should be deleted. Instead of just one singleresult, this embodiment monitors more than once the student's behavior,which enhances identifying a pattern to eliminate outlying points.

The monitoring step does not have to stop after monitoring twice. Themonitoring step can continue in a periodic manner, such as once everytwo seconds. In the embodiments of monitoring more than once ormonitoring periodically, the results can be analyzed to identifypatterns.

The behavior monitored more than once can be of the same type, or can beof different types. In one embodiment, in monitoring more than once, thesensor monitors the same type of behavior each time. In anotherembodiment, in monitoring more than once, the sensor monitors more thanone type of behavior; for example, a first monitoring process is on onetype of behavior, and a second monitoring process is on another type ofbehavior. In monitoring more than one type of behavior, the sensor mayinclude more than one type of sensor, which can monitor more than onetype of behavior substantially simultaneously. Monitoring more than onetype of behavior is similar to monitoring one type of behavior more thanonce, in the sense that both approaches increase the accuracy indetermining the student's concentration level.

FIG. 4 shows examples of different types of concentration-sensitivebehavior, which are volitional 300. In one embodiment, the sensor 110monitors the student's volitional inputs entered into the computer (box302). One type of volitional inputs is entered through the keyboard 176or the mouse 182. The study materials can be presented to the studentthrough the monitor 178. As the student works on the study materials, heenters commands through the keyboard 176 or a position-pointing device,such as the mouse 182, or arrow buttons of the keyboard 176. The inputsmay be the downward or upward arrows on the keyboard or the mouse, ormay be the typing speed through the keyboard.

In one embodiment, the sensor 110 monitors the speed of inputs by thestudent as a function of time. There are different ways to monitor thespeed of inputs, such as polling periodically the corresponding devicesof those inputs. Such monitoring process should be obvious to thoseskilled in the art, and will not be further described.

As the student starts working on the study materials, the inputs areentered at a certain speed. As the student gets tired, or as the studentloses concentration, this speed typically decreases. In this embodiment,the student's input speed is compared with a reference speed to identifychanges.

There are a number of methods to determine the reference speed. In oneembodiment, this reference speed is set through randomly sampling manystudents. Based on the students' responses on similar study materials, areference speed is determined. In another embodiment, the student'sinitial speed becomes the reference speed. This initial speed may befound for example by averaging the student's speed across five minutes,such as from the first one minute to the first six minutes of thestudent's usage.

Different types of study materials typically have different referencespeeds. For example, if the study materials include no pictures, theinput speed may be slow because the student has to read an entire screenof text. If the student has to compose a sentence, the speed is likelyto have frequent short pauses because the student has to think tocompose the sentence. To accommodate such variations, in one embodiment,the reference speed is a function of the difficulty level of the studymaterials. As the student progresses in working on the study materials,the difficulty level of the study materials typically increases. In oneembodiment, the reference speed is divided by the following factor:

(The difficulty level of the study material * a constant).

With the above equation, as the difficulty level increases, thereference speed decreases accordingly. In this embodiment, the referencespeed tracks the difficulty level of the study materials.

As discussed above, by monitoring the speed of the student's inputs, thesystem 100 can provide an indication of the student's concentration.Thus, one rule is as follows:

If the speed of the student's volitional inputs across a predeterminedperiod of time is significantly lower than the reference speed, thestudent has lost concentration in the study materials.

In one embodiment, the predetermined period of time is two minutes; andmore than three times slower is considered as significantly lower.

In another embodiment, the study materials are presented through amulti-windows environment. The student enters inputs into the system,such as through a position-pointing device, like the mouse 182, orthrough the keyboard 176. In one embodiment, the sensor 110 in thisembodiment is implemented through software, which periodically, such asevery two seconds, polls the operating system or the device drivers ofthe position-pointing device. The polling determines if there have beenany inputs. Writing such software to monitor such inputs to the systemshould be obvious to those skilled in the art, and will not be furtherdescribed in this application. In such an embodiment, one rule is asfollows:

If for a predetermined period of time, the inputs have been enteredoutside the window where the study materials reside, the student haslost concentration in the study materials.

In yet another embodiment, the study materials are presented in a windowenvironment that has a focus window, and the sensor 110 can sense thefocus window, for example as in the above embodiment. In such anembodiment, one rule is as follows:

If the study materials are not in the focus window for a predeterminedperiod of time, the student has lost concentration in the studymaterials.

In one embodiment, the predetermined amount of time is more than oneminute. If monitoring is performed every three seconds, in one minute,the system would have performed 20 measurements.

In yet another embodiment, the sensor 110 senses another type ofvolitional behavior, which is based on the student's face. In thisembodiment, the monitor 178 presents study materials. The sensor 110including the digital camera 180 are positioned adjacent to the monitor178, as shown, for example in FIG. 2A. With the camera positioned whereit is, when the student is looking at the monitor to work on the studymaterials, the digital camera 180 could take digital images of thestudent's face. Taking the digital images to generate numerous bits ofdata should be obvious to those skilled in the art and will not befurther described in this application.

To improve the performance of this embodiment, before the step ofmonitoring, the present invention includes the step of calibrationthrough imaging. One calibration technique enters the student's imagebefore the student works on the study materials, and uses that image asthe reference to compare with other images. For example, before thestudent starts working on the study materials, he is asked to look atthe monitor 178 with a message box having a message such as “LOOK ATME,” and with a picture of two eyes staring at the student. Then, thedigital camera 180 takes a reference image of the student's face, whotypically looks at the two eyes.

The reference image should be analyzed. That image includes not only thestudent's face, but also background information, such as the wall of aroom. In one embodiment, the controller assumes that the student's twoeyes are looking at the two eyes in the monitor. Based on thisassumption, the student's face is determined. Such image recognitiontechniques are disclosed for example in “Computer Recognition of HumanFaces,” written by Takeo Kanada, and published by Birkhauser Verlag,Basel and Stuttgart, in 1977. Even if the distance between the monitorand the student's face increases, the relative distances among differentfeatures on his face remain the same. In one embodiment, the monitoringstep focuses on relative distances to re-calibrate the student's face.Such image recognition techniques should be obvious to those skilled inthe art, and will not be further described in the present application.

One type of facial information is the facial orientation (box 304). Thecontroller 104 connected to the digital camera 180 calibrates the facialorientation when the student is looking at the monitor 178. Thisreference image could be just the oblong shape of the face. Aftercalibration, when the student starts working on the study materials, thedigital camera 180 regularly captures the facial image, such as onceevery few seconds. All information in that image is removed leavingbehind the orientation of the face. These orientations are compared withthe reference image to check for differences. The distance between themonitor and the student's face may change. To compensate for suchchanges, in one embodiment, the controller uses the ratio of the longesthorizontal to the longest vertical distance of the oblong shape. If thecaptured facial orientation is significantly different from thereference facial orientation, the student is not looking at the monitor.The student may be looking away from the computer or drooping whilefalling asleep. In such an embodiment, one rule is as follows:

If the student's facial orientation is significantly different from itsreference image as shown in two consecutive monitoring processes, thestudent has lost concentration in the study materials.

In one embodiment, two images are considered significantly different iftheir horizontal-to-vertical-distance ratios differ by more than 20%.

Another type of facial information is the condition of the eyes (box306). If the eyelids are covering significant portions of the irises,the student's eyes are closing. In such an embodiment, one rule is asfollows:

If the eyelids cover more than 60% of the irises as shown in twoconsecutive monitoring processes, the student has lost concentration inthe study materials.

Another type of facial information is the student's facial expressions(box 308), such as whether the student is frowning or not. In such anembodiment, one rule is as follows:

If the student frowns in two consecutive monitoring processes, thestudent is concentrating on the study materials.

Concentration-sensitive behavior can be involuntary. In one embodiment,the sensor 110 monitors the sizes of the student's pupils, assuming thata student's pupil dilates if the student loses focus and concentration.In such an embodiment, one rule is as follows:

If the average size of the student's pupils dilates by more than 20% ascompared to the average size of the reference image for a predeterminedamount of time, the student has lost concentration in the studymaterials.

Other examples of involuntary concentration-sensitive behavior includethe student's heart beat, breathing rate, body temperature and whetherthe student's sweat has increased. With appropriate sensors and rules,these involuntary behavior can be monitored to provide indications onwhether the student has lost concentration in the study materials.

There are many other types of concentration-sensitive behavior.Different types of behavior coupled with their corresponding sensors andrules should be able to indicate the student's concentration level.

More than one type of the student's concentration-sensitive behavior canbe monitored by one or more sensors. In fact, one type can bevolitional, with the other type involuntary. Including different typesof behavior tends to increase the accuracy of identifying the student'sconcentration level. With more than one type of behavior beingmonitored, the system may not have to monitor each type of behavior morethan once to identify the student's concentration level. An example of arule for such an embodiment is as follows:

If the student's facial orientation is different from the referenceimage by more than 20% while the student's eyelids are covering morethan 60% of the irises, the student has lost concentration in the studymaterials.

Such rules should be obvious to experts in the field of humanperception, and will not be further described in this application.

The above embodiments describe whether the student has lostconcentration or not. However, the invention is also applicable toindicate the student's degree of concentration, such as ranging fromlow, medium to high. For example, if the student has not lostconcentration in the study materials for a long period of time, thestudent's concentration level is high. Another example is that if thestudent's eyes are wide open with his inputs through the mouse movingdown the study materials in a fairly constant speed for a long durationof time, such as five minutes, the student's concentration level is alsohigh.

In another embodiment, if the controller 104 decides that the studenthas not lost concentration for a long period of time, such as tenminutes, the controller 104 averages the captured results during thattime frame—with outlying points removed--and treats the averaged resultsas the reference, which will be used to compare with subsequent capturedresults, to determine if the student has lost concentration in the studymaterials. The reference can be a reference image, such as the student'sface, or the student's input speed, as appropriately modified by thestudy materials' difficulty level, or other monitored results. As thestudent continues working on study materials, this reference can beupdated regularly by averaging it with subsequent captured results,which also show that the student has not lost concentration. Unlike manyof the previously described references, which are static, this type ofreference is typically not a constant, and is known as a dynamicreference. It is usually more closely tailored to the student. With moredata used to generate the dynamic reference, its accuracy is typicallybetter than the static references.

In yet another embodiment, the system 100 asks for the student'sidentity, such as the student's name, when the student starts working onthe study materials. After the student enters his identity, it is storedin the system 100. The student's reference information, whether staticor dynamic, is stored with the student's identity in the memory of thesystem 100, such as its harddisk. After the first working session, ifthe student wants to work on study materials through the system 100again, the system retrieves from its memory the student's referenceinformation. For such an embodiment, the retrieved reference informationcan replace the step of calibration. If the reference is of the dynamictype, the retrieved information is regularly updated.

Based on one or more of the above concentration-sensitive behaviorcoupled to one or more appropriate rules, the indicator 114 provides anindication on the student's concentration (step 258), or the student'sdegree of concentration. Such indication can be as simple as changingthe state of a register—a high logic level indicates the student has notlost concentration, while a low logic level indicates the student has.Another indication can be printing a report indicating that thestudent's degree of concentration in the study materials for a period oftime.

In one embodiment, the system reacts according to the indication (step260). Some examples of reactions include stimulation, rewards,punishments or changing the study materials.

If the indication is that the student has lost concentration in thestudy materials, one way the controller 104 can help the student tore-focus on the study materials is through stimulation. This includespresenting a real-life application of the study materials that thestudent has lost concentration in. The stimulation can be through sound.It can be visual effects, including changing the screen temporarily andthen restoring to the previous screen.

Another type of stimulation includes allowing the student to play agame. This stimulation is applicable if the student has been working onthe study materials for a long duration of time, and should have abreak. Thus, after the student has worked for a long period of time,such as 45 minutes, and is losing concentration in the study materials,the controller can pose the student a question, such as, “Do you want totake a break and play a game?” If the student wants to, in oneembodiment, the controller accesses a game from the study-materialsstorage medium, which includes a number of games. The game serves as adiversion. Not only does it distract the student's mind for some time,the game also relaxes and entertains the student. After the game,presentation is resumed on the study materials.

Another form of reaction is a reward. If the student has beenconcentrating for a long period of time, at the end of a section in thestudy materials, the system reacts by praising the student audiblythrough a speaker, or visually through the monitor with words like “TIMEFOR A SNACK!” Other examples of rewards include playing a short piece ofmusic, presenting a joke, a factoid on an interesting subject, orplaying a short animation or video clip.

A further form of reaction is punishment. This includes generating areport indicating that the student has lost concentration for a longperiod of time so that the student's supervisor can punish the studentaccordingly. Another punishment may be an audible reprimand, such as“PAY ATTENTION!”

The system can also change the study materials according to themonitored results. If the student has lost concentration in working onthe study materials for a predetermined amount of time, the system canreact by changing the study materials to a different set of materials.Also, the presenter 106 may change the presentation style accordingly,such as by reducing the speed of presentation through increasing theline spacing of the text or the size of the image to present to thestudent.

In yet another embodiment, due to the indication, the system asks thestudent a question. This question can stimulate the student, and helpthe student to re-focus in the study materials. Typically, the questionis based on the study materials just presented to the student.

As a side note, while the controller 104 through the sensor 110 monitorsthe student's concentration-sensitive behavior, the controller 104 canalso track the corresponding study materials being presented to thestudent. Such an embodiment has the added benefit of tying theindication with the corresponding study materials presented to thestudent.

Back to the embodiment that asks the student a question, this embodimentcan be achieved, for example, through the selector 102 sending to thestudy-materials storage medium 108 the line-item root of the studymaterials just presented. From the line-item root, a set of questionswith the same line-item root is retrieved, and one of those question israndomly selected for the student. Other ways may be used to generate aquestion on materials just presented to the student. One simple way isto randomly select a sentence that has just been presented to thestudent, and change the syntax of that sentence into a question.

The embodiment on asking questions has a number of benefits. Even if thestudent does not know the answer to the question, typically, the studentis stimulated by the question. Also, the question can be used to assessthe student's understanding level on the materials just presented to thestudent. After the student answers the question, if the answer iscorrect, the controller 104 can praise the student appropriately. If theanswer is not correct, the student may not understand what has just beenpresented. The controller 104 has a number of options. For example, thestudy materials just presented can be presented to the student again;the location as to where he can find the answer to the question can bepresented to the student; the location of the answer can be hyperlinkedto the location of the wrong answer if the student activates an iconshown on the presenter 106; the presenter 106 presents study materialsthat are easier than the one just presented to the student, such as onewith a lower difficulty level; or the presenter 106 can resumepresenting, and ignore the wrong answer altogether.

The above embodiment on asking questions can be modified to focus onincreasing the student's concentration level. FIG. 5 shows such anembodiment 350. The system presents (step 352) study materials to thestudent. Then, the system asks the student a question unexpectedly (step354). As an example, if the study material is presented through themonitor, unexpectedly, the entire screen changes. From a screen of studymaterials, the system suddenly changes the screen to display a question.The unexpected nature of the change, together with the displaying of thequestion stimulate the student. To further enhance the effect ofstimulation, the system can spell out the question while displaying it.Typically the question is based on the study materials the student hasbeen working on. After the student responds to the question, the systemresumes (step 356) presenting the study materials to the student.

The question stimulates. Right before the question is presented, thestudent may be concentrating or may not be concentrating. Either way,the student, unlikely to be aware that a question is coming, is suddenlyconfronted with a question. Independent of whether the student knows theanswer, the question typically increases the student's concentrationlevel. Also, responding to a question is an active learning approach, ascompared to the passive learning approach of reading. The more activelearning approach together with the unexpected nature of the questiontend to increase the student's memory retention in the subject mattercovered by the question.

Another benefit provided by the question is that the student's answer tothe question provides an indication on the student's understanding levelin the study materials. As described above, if the answer is wrong, thesystem can go over that part of the study materials, or can reduce thedifficulty levels of the study materials to be presented to the student.In another embodiment, the question is just for increasingconcentration; the system ignores the answer, and continues on with thepresentation.

The student might have stopped working on the study materialsaltogether. For the embodiment that monitors the student's inputs, ifthere is no inputs for a predetermined amount of time, such as tenminutes, the system assumes that the student has totally stopped workingon the study materials.

The present invention teaches sensing through different types ofnon-intrusive sensors, which are defined as sensors that do not causethe student physical pain and suffering when they are sensing thestudent's concentration-sensitive behavior. As technology progresses,sensors that are intrusive today can become non-intrusive in the future,for example, sensors that monitor the student's brain waves, which canbe a type of concentration-sensitive behavior.

Rules are stored in the rules storage medium. However, in oneembodiment, the rules have previously been embedded in the softwareimplementing the present invention. With rules already embedded in thesoftware, there is no need for accessing the rules, and there is no needfor the system to have the rules storage medium.

In the above embodiments, the student's behavior is monitored more thanonce before the step of analysis. In another embodiment, the monitoringstep and the analysis step are intermixed. Instead of monitoring morethan once and then analyzing the results, in this embodiment, the sensormonitors one type of behavior, with the result analyzed. Then the sensormonitors the same or a different type of behavior, with the resultanalyzed.

In yet another embodiment, the steps in the present invention repeat.For example, after the step of reacting according to the indication(step 260) or providing an indication (step 258), the invention repeatsfrom the step of monitoring automatically (step 254). In thisembodiment, study materials are continually presented to the student,although the study materials might be changed due to the reaction (step260).

The rules discussed can be self-adapting. In other words, the controller104 can change a rule after applying the rule to a number of situationsand after analyzing the results. This can be done, for example, in afussy-logic system.

Other embodiments of the invention will be apparent to those skilled inthe art from a consideration of this specification or practice of theinvention disclosed herein. It is intended that the specification andexamples be considered as exemplary only, with the true scope and spiritof the invention being indicated by the following claims.

1. A computing device comprising: a display; an imaging sensor to sensea first feature of a user regarding a first volitional behavior of theuser to produce a first set of measurements, the imaging sensor detachedfrom the first feature to sense the first feature, the first featurebeing related to an attribute of the head of the user, and the first setof measurements including a plurality of images of the first feature;and a processor coupled to the imaging sensor and the display, theprocessor to analyze at least the first set of measurements to identifya speed of the user to view content presented by the display.
 2. Acomputing device as recited in claim 1, wherein the processor isconfigured to determine what is to be presented by the display in viewof the analysis.
 3. A computing device as recited in claim 2, wherein todetermine what is to be presented depends on comparing the speed with areference speed.
 4. A computing device as recited in claim 3, whereinthe reference speed is a speed of the user.
 5. A computing device asrecited in claim 4, wherein the reference speed depends on at least aspeed of another user.
 6. A computing device as recited in claim 1,wherein to analyze at least the first set of measurements includes toidentify a width of the head.
 7. A computing device as recited in claim6 wherein to analyze at least the first set of measurements includes toidentify a height or a vertical distance of the head.
 8. A computingdevice as recited in claim 6, wherein to analyze at least the first setof measurements includes to determine a change in the identified widthof the head based on at least two images of the user.
 9. A computingdevice as recited in claim 8, wherein what is to be presented by thedisplay depends on the change determined.
 10. A computing device asrecited in claim 1, wherein the computing device to allow the user toread content presented by the display at least based on the first set ofmeasurements.
 11. A computing device as recited in claim 1, wherein theimaging sensor to sense another feature of the user regarding anothervolitional behavior of the user to produce another set of measurements,the another feature being different from the first feature and theanother feature being related to an attribute of at least one eye of theuser, and wherein the processor to determine, based on the first set ofmeasurements and the another set of measurements, what is to bepresented by the display for the user.
 12. A computing device as recitedin claim 1, wherein the computing device to sense another feature of theuser regarding another volitional behavior of the user to produceanother set of measurements, wherein the another volitional behavior tohelp control movement of content on the display as the content ispresented by the display, and wherein the processor to determine, basedon the first set of measurements and the another set of measurements,what is to be presented by the display for the user.
 13. A computingdevice comprising: a display to show content at least during some of thetime the device is used by a user; an imaging sensor to sense a firstfeature of the user regarding a first volitional behavior of the user toproduce a first set of measurements, the imaging sensor detached fromthe first feature to sense the first feature, the first feature beingrelated to an attribute of the head of the user, and the first set ofmeasurements including an image of the first feature; and a processorcoupled to the imaging sensor and the display, the processor to: analyzeat least the first set of measurements, with the analyzing being;determine whether to change what is to be presented by the display inview of the analysis; change what is to be presented by the display atleast in view of the determination; and resume what is to be presentedby the display at least in view of a second set of measurements fromsensing the user by the device.
 14. A computing device as recited inclaim 13, wherein to change includes to stop what the display has beenpresenting.
 15. A computing device as recited in claim 13, wherein thefirst set of measurements includes a plurality of images of the firstfeature.
 16. A computing device as recited in claim 15, wherein theprocessor to analyze the first set of measurements to identify a speedof the user to view content presented by the display.
 17. A computingdevice as recited in claim 16, wherein to determine whether to changewhat is to be presented depends on comparing the speed with a referencespeed.
 18. A computing device as recited in claim 13, wherein to changeincludes to change a visual effect of the display.
 19. A computingdevice as recited in claim 18, wherein to resume includes to restore thedisplay back to a previous screen.
 20. A computing device as recited inclaim 13, wherein the processor to link the first set of measurements toan identity of the user.
 21. A computing device as recited in claim 13,wherein the imaging sensor to sense another feature of the userregarding another volitional behavior of the user to produce another setof measurements, the another feature being different from the firstfeature and the another feature being related to an attribute of atleast one eye of the user, and wherein to determine whether to changealso depends on the another set of measurements.
 22. A computing deviceas recited in claim 21, wherein the attribute of the at least one eyeincludes the pupil of the at least one eye.
 23. A computing device asrecited in claim 13, wherein the computing device sense another featureof the user regarding another volitional behavior of the user to produceanother set of measurements, and wherein the another volitional behaviorto help control movement of content on the display as the content ispresented by the display.
 24. A computing device as recited in claim 4,wherein the reference speed is a static reference speed.
 25. A computingdevice as recited in claim 4, wherein the reference speed is a dynamicreference speed.
 26. A computing device as recited in claim 11, whereinthe computing device to sense features of different behaviors and toanalyze the sensed results in a manner that is intermixed.
 27. Acomputing device as recited in claim 1, wherein the processor further toprovide an indication to the user regarding the device sensing the user.28. A computing device as recited in claim 1, wherein to analyze atleast the first set of measurements includes to self-adapt based onmeasurements.
 29. A computing device as recited in claim 17, wherein thereference speed is a static reference speed.
 30. A computing device asrecited in claim 17, wherein the reference speed is a dynamic referencespeed.
 31. A computing device as recited in claim 21, wherein thecomputing device to sense features of different behaviors and to analyzethe sensed results in a manner that is intermixed.
 32. A computingdevice as recited in claim 13, wherein the processor further to providean indication to the user regarding the device sensing the user.
 33. Acomputing device as recited in claim 13, wherein to analyze at least thefirst set of measurements includes to self-adapt based on measurements.34. A computing device comprising: a display; an imaging sensor attachedto the display to sense a first feature of a user regarding a firstvolitional behavior of the user to produce a first set of measurements,the imaging sensor detached from the first feature to sense the firstfeature, the first feature being related to an attribute of the head ofthe user, and the first set of measurements including a plurality ofimages of the first feature; and a processor coupled to the imagingsensor and the display, the processor to analyze, relative to a windowat the display, at least the first set of measurements to identifywhether the user is not paying attention to content in the windowpresented by the display.
 35. A computing device as recited in claim 34,wherein the processor to determine what is to be presented by thedisplay in view of the analysis.
 36. A computing device as recited inclaim 35, wherein to determine what is to be presented depends on aspeed of an action by the user.
 37. A computing device as recited inclaim 36, wherein the speed of the user action depends on a calibrationprocess on the user action.
 38. A computing device as recited in claim37, wherein the calibration process depends on at least a speed of anaction of another user.
 39. A computing device as recited in claim 34,wherein to analyze at least the first set of measurements includes toidentify a width of the head.
 40. A computing device as recited in claim39, wherein to analyze at least the first set of measurements includesto identify a height or a vertical distance of the head.
 41. A computingdevice as recited in claim 39, wherein to analyze at least the first setof measurements includes to determine a change in the identified widthof the head based on at least two images of the user.
 42. A computingdevice as recited in claim 41, wherein what is to be presented by thedisplay depends on the change determined.
 43. A computing device asrecited in claim 34, wherein the computing device to allow the user toread content presented by the display at least based on the first set ofmeasurements.
 44. A computing device as recited in claim 34, wherein theimaging sensor to sense another feature of the user regarding anothervolitional behavior of the user to produce another set of measurements,the another feature being different from the first feature and theanother feature being related to an attribute of at least one eye of theuser, and wherein the processor to determine, based on the first set ofmeasurements and the another set of measurements, what is to bepresented by the display for the user.
 45. A computing device as recitedin claim 34, wherein the computing device to sense another feature ofthe user regarding another volitional behavior of the user to produceanother set of measurements, wherein the another volitional behavior tohelp control movement of content on the display as the content ispresented by the display, and wherein the processor to determine, basedon the first set of measurements and the another set of measurements,what is to be presented by the display for the user.
 46. A computingdevice as recited in claim 37, wherein the calibration process comprisesa static reference speed.
 47. A computing device as recited in claim 37,wherein the calibration process comprises a dynamic reference speed. 48.A computing device as recited in claim 45, wherein the computing deviceto sense features of different behaviors and to analyze the sensedresults in a manner that is intermixed.
 49. A computing device asrecited in claim 34, wherein the processor further to provide anindication to the user regarding the device sensing the user.
 50. Acomputing device as recited in claim 34, wherein to analyze at least thefirst set of measurements includes to self-adapt based on measurements.